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What you should be familiar with kid's COVID-19: a systematic evaluation.
Patients with pre-admission OAT (adjusted odds ratio [AOR] = 15.30; 95% CI [13.2, 17.7]), acute OUD diagnosis (AOR = 2.3; 95% CI [1.99, 2.66]), and male gender (AOR 1.52; 95% CI [1.16, 2.01]) had increased odds of OAT receipt. Patients who received non-OAT opioids (AOR 0.53; 95% CI [0.46, 0.61]) or surgical procedures (AOR 0.75; 95% CI [0.57, 0.99]) had decreased odds of OAT receipt. Large-sized (AOR = 2.0; 95% CI [1.39, 3.00]) and medium-sized (AOR = 1.9; 95% CI [1.33, 2.70]) hospitals were more likely to provide OAT. CONCLUSIONS In a sample of VHA inpatient medical admissions, OAT delivery was infrequent, varied across the health system, and was associated with specific patient and hospital characteristics. Policy and educational interventions should promote hospital-based OAT delivery.BACKGROUND Group-based lifestyle change programs based on the Diabetes Prevention Program (DPP) are associated with clinically significant weight loss and decreases in cardiometabolic risk factors. However, these benefits depend on successful real-world implementation. Studies have examined implementation in community settings, but less is known about integration in healthcare systems, and particularly in large, multi-site systems with the potential for extended reach. OBJECTIVE To examine the barriers and facilitators to successful DPP implementation in a large multi-site healthcare system. DESIGN Semi-structured interviews, based on the RE-AIM framework, were conducted in person for 30-90 min each. PARTICIPANTS Past and present DPP lifestyle coaches in the healthcare system identified using purposive sampling. APPROACH Thematic analysis of qualitative data to identify key factors influencing the success of DPP implementation. An iterative consensus process was used to model the relationships among factors. ective of lifestyle coaches. With further examination, the conceptual model presented here may be used for planning and managing the implementation of group-based behavioral interventions in these settings.BACKGROUND Women providers have a more patient-centered communication style than men, and some studies have found women primary care providers are more likely to meet quality performance measures. OBJECTIVE To explore gender differences in the quality of primary care process and outcome measures. DESIGN Retrospective analysis of primary care performance data from 1 year (2018-2019). PARTICIPANTS A total of 586 primary care providers (311 women and 275 men) who cared for 241,428 primary care patients at 96 primary care clinics at 8 Veterans Affairs (VA) medical centers. selleck chemicals llc MAIN MEASURES Our primary outcome was a composite quality measure that averaged all thirty-four primary care performance measures that assessed performance in cancer screening, diabetes care, cardiovascular care, tobacco counseling, risky alcohol screening, immunizations, HIV testing, opiate care, and continuity. Our secondary outcomes were performance on each of the 34 measures. KEY RESULTS There was no difference in the average performance on our composite measure between men and women (75.8% vs. 76.6%, p = 0.17). Among the 34 primary care quality measures collected, there was no difference between male and female providers' performance. Using a more conservative cut-point, women were more likely to screen at-risk diabetic patients for hypoglycemia and document follow-up on risky alcohol behavior noted during patient check-in. These differences were clinically small and likely due to chance, given the multiple measures evaluated in this study. CONCLUSIONS We found little evidence of difference in the performance on primary care quality measures between male and female providers.BACKGROUND Research comparing direct-acting oral anticoagulants (DOACs) to warfarin has excluded nursing home residents, a vulnerable and high-risk population. OBJECTIVE To compare the safety and effectiveness of DOACs versus warfarin. DESIGN New-user cohort study (2011-2016). PATIENTS US nursing home residents aged > 65 years with non-valvular atrial fibrillation enrolled in fee-for-service Medicare for > 6 months. EXPOSURES Initiators of DOACs (2881 apixaban, 1289 dabigatran, 3735 rivaroxaban) were 11 propensity matched to warfarin initiators. MAIN MEASURES Outcomes included ischemic stroke or transient ischemic attack (i.e., ischemic cerebrovascular event), bleeding (extracranial or intracranial), other vascular events, death, and a composite of all outcomes. Absolute rate differences (RD) and cause-specific hazard ratios (HR) with 95% confidence intervals (CI) were estimated. Subgroup analyses were performed by alignment of DOAC dosing with labeling. KEY RESULTS Median age (84 years), CHA2DS2-Vasc (5), anates of adverse outcomes including mortality compared with warfarin users.BACKGROUND The patient-centered medical home (PCMH) model is intended to improve primary care, but evidence of its effects on provider well-being is mixed. Investigating the relationships between specific PCMH components and provider burnout and potential attrition may help improve the efficacy of the care model. OBJECTIVE We analyzed provider attitudes toward specific components of PCMH in the Veterans Health Administration (VA) and their relation to emotional exhaustion (EE)-a central component of burnout-and intent to remain in VA primary care. DESIGN Logistic regression analysis of a cross-sectional survey. SUBJECTS 116 providers (physicians; nurse practitioners; physician assistants) in 21 practices between September 2015 and January 2016 in one VA region. MAIN MEASURES Outcomes burnout as measured with the emotional exhaustion (EE) subscale of the Maslach Burnout Inventory and intent to remain in VA primary care for the next 2 years; predictors difficulties with components of PCMH, demographic characteristics. KEY RESULTS Forty percent of providers reported high EE (≥ 27 points) and 63% reported an intent to remain in VA primary care for the next 2 years. Providers reporting high difficultly with PCMH elements were more likely to report high EE, for example, coordinating with specialists (odds ratio [OR] 8.32, 95% confidence interval [CI] 3.58-19.33), responding to EHR alerts (OR 6.88; 95% CI 1.93-24.43), and managing unscheduled visits (OR 7.53, 95% CI 2.01-28.23). Providers who reported high EE were also 87% less likely to intend to remain in VA primary care. CONCLUSIONS To reduce EE and turnover in PCMH, primary care providers may need additional support and training to address challenges with specific aspects of the model.
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